Lecturer


School of Information and Communication Technology (SOICT)
Hanoi University of Science and Technology (HUST)

Research

Interests

Publications

Journal

  1. Hai Nam Le, Trang Nguyen, Linh Ngo Van, Thien Huu Nguyen, and Khoat Than. "Continual variational dropout: a view of auxiliary local variables in continual learning." Machine Learning 113, no. 1 (2024): 281-323.
  2. Nguyen Tung, Trung Mai, Nam Nguyen, Linh Ngo Van, Khoat Than. "Balancing stability and plasticity when learning topic models from short and noisy text streams." Neurocomputing, 2022.
  3. Ha Nguyen, Hoang Pham, Son Nguyen, Linh Ngo Van, Khoat Than. "Adaptive Infinite Dropout for Noisy and Sparse Data Streams," Machine Learning journal, 2022.
  4. Quyen Tran, Lam Tran, Linh Chu Hai, Linh Ngo, Khoat Than. “From Implicit to Explicit feedback: A deep neural network for modeling sequential behaviors and long-short term preferences of online users”. Neurocomputing, 479, pp.89-105, 2022.
  5. Bach, Tran Xuan, Nguyen Duc Anh, Linh Ngo Van, Khoat Than. “Dynamic transformation of prior knowledge into Bayesian models for data streams.” IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
  6. Linh Ngo Van, Bach Tran, Khoat Than. “A graph convolutional topic model for short and noisy text streams” Neurocomputing, Volume 468, Pages 345-359, 2022.
  7. Dieu Vu, Khang Truong, Khanh Nguyen, Linh Ngo Van, Khoat Than, “Revisiting Supervised Word Embeddings”, Journal of Information Science and Engineering, 38(2), 2022.
  8. Tien-Cuong Nguyen, Van-Quyen Nguyen, Van-Linh Ngo, Khoat Than, Tien-Lam Pham. “Learning Hidden Chemistry with Deep Neural Networks”. Computational Materials Science journal, Volume 200, December 2021, 110784. Elsevier.
  9. Duc-Anh Nguyen, Ngo Van Linh, Nguyen Kim Anh, Canh Hao Nguyen, Khoat Than, “Boosting prior knowledge in streaming variational Bayes,” Neurocomputing, Volume 424, 1 February 2021, Pages 143-159.
  10. Anh Tuan Phan, Bach Tran, Thien Huu Nguyen, Linh Van Ngo, Khoat Than, “Bag of biterms modeling for short texts”, Knowledge and Information Systems (KAIS),62, pages 4055–4090 (2020).
  11. Ngo Van Linh, Duc Anh Nguyen, Binh Nguyen, Khoat Than, “Neural Poisson Factorization,” IEEE Access, 2020.
  12. Cuong Ha-Nhat, Dang Tran, Linh Ngo Van, Khoat Than, “Eliminating overfitting of probabilistic topic models on short and noisy text: The role of Dropout”, International Journal of Approximate Reasoning, Springer, 2019.
  13. Hoa Le Minh, Son Ta Cong, Quyen Pham The, Ngo Van Linh, Khoat Than, “Collaborative Topic Model for Poisson distributed ratings”, International Journal of Approximate Reasoning (IJA), 2018.
  14. Ngo Van Linh, Nguyen Kim Anh, Khoat Than, Chien Nguyen Dang, “An Effective and Interpretable Method for Document Classification”, Knowledge and Information Systems journal (KAIS), 50(3), 763-793, 2017.

Conference

  1. Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen, Trang Pham, Linh Van Ngo, Nhat Ho,"Mixture of experts meets prompt-based continual learning", NeurIPS 2024
  2. Quyen Tran, Nguyen Xuan Thanh, Nguyen Hoang Anh, Nam Le Hai, Trung Le, Linh Van Ngo, Thien Huu Nguyen, “Preserving Generalization of Language models in Few-shot Continual Relation Extraction”, In Proceeding of the Conference on Empirical Methods in Natural Language Processing, 2024
  3. Duy-Tung Pham, Thien Trang Nguyen Vu, Tung Nguyen, Linh Van Ngo, Duc Anh Nguyen, Thien Huu Nguyen, “NeuroMax: Enhancing Neural Topic Modeling via Maximizing Mutual Information and Group Topic Regularization”, In Findings of the Conference on Empirical Methods in Natural Language Processing, 2024
  4. Viet Dao, Van-Cuong Pham, Quyen Tran, Thanh-Thien Le, Linh Ngo Van, Thien Huu Nguyen, “Lifelong Event Detection via Optimal Transport”, In Proceeding of the Conference on Empirical Methods in Natural Language Processing, 2024
  5. Luong, Tinh Son, Thanh-Thien Le, Linh Ngo Van, and Thien Huu Nguyen. "Realistic Evaluation of Toxicity in Large Language Models." Findings of the Association for Computational Linguistics ACL, pp.1038-1047 (2024).
  6. Man Hieu, Chien Van Nguyen, Nghia Trung Ngo, Linh Ngo, Franck Dernoncourt, and Thien Huu Nguyen. "Hierarchical Selection of Important Context for Generative Event Causality Identification with Optimal Transports." In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pp. 8122-8132. 2024.
  7. Le Thanh-Thien, Manh Nguyen, Tung Thanh Nguyen, Linh Ngo Van, and Thien Huu Nguyen. "Continual relation extraction via sequential multi-task learning." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 16, pp. 18444-18452. 2024.
  8. Le Thanh-Thien, Viet Dao, Linh Nguyen, Thi-Nhung Nguyen, Linh Ngo, and Thien Nguyen. "SharpSeq: Empowering Continual Event Detection through Sharpness-Aware Sequential-task Learning." In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pp. 3632-3644. 2024.
  9. Nguyen, Huy, Chien Nguyen, Linh Ngo, Anh Luu, and Thien Nguyen. "A spectral viewpoint on continual relation extraction." In Findings of the Association for Computational Linguistics: EMNLP 2023, pp. 9621-9629. 2023.
  10. Chien Nguyen, Linh Ngo Van and Thien Huu Nguyen. “Retrieving Relevant Context to Align Representations for Cross-lingual Event Detection”. In Findings of the Association for Computational Linguistics: ACL 2023
  11. Viet Dac Lai, Hieu Man, Linh Ngo, Franck Dernoncourt and Thien Huu Nguyen. “Multilingual SubEvent Relation Extraction: A Novel Dataset and Structure Induction Method”. In Findings of the Association for Computational Linguistics: EMNLP 2022 (pp. 5559-5570).
  12. Nghia Ngo Trung, Linh Ngo Van, and Thien Huu Nguyen. “Unsupervised Domain Adaptation for Text Classification via Meta Self-Paced Learning”, Proceedings of COLING 2022
  13. Linh Ngo Van, Nam Le Hai, Hoang Pham, Khoat Than. “Auxiliary Local Variables for Improving Regularization/prior Approach in Continual Learning”. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2022.
  14. Hoang Phan Viet, Anh Phan Tuan, Son Nguyen, Linh Ngo Van, Khoat Than. “Reducing catastrophic forgetting in neural networks via Gaussian mixture approximation”. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2022.
  15. Hieu Man Duc Trong, Nghia Ngo Trung, Linh Ngo Van and Thien Huu Nguyen "Selecting Optimal Context Sentences for Event-Event Relation Extraction" Proceedings of AAAI 2022, Vancouver, Canada, February 2022
  16. Tuc Nguyen, Linh Ngo Van, Khoat Than, “Modeling the sequential behaviors of online users in recommender systems”, In Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications. 2020.
  17. Van-Son Nguyen, Duc-Tung Nguyen, Linh Ngo Van, Khoat Than, “Infinite Dropout for training Bayesian models from data streams”, In Proceedings of IEEE International Conference on Big Data (BigData 2019), Los Angeles, CA, USA, 2019.
  18. Tuan Anh Phan, Nhat Nguyen Trong, Duong Bui, Linh Van Ngo, and Khoat Than, “From Implicit to Explicit Feedback: A deep neural network for modeling the sequential behaviors of online users”, In Proceeding of the Asian Conference on Machine Learning (ACML), 2019.
  19. Linh The Nguyen, Linh Van Ngo, Khoat Than and Thien Huu Nguyen, “Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings”, In Proceeding of the Association for Computational Linguistics (ACL), 2019.
  20. Thanh Hai Hoang, Anh Phan Tuan, Linh Ngo Van, Khoat Than, “Enriching user representation in Neural Matrix Factorization”, In Proceedings of RIVF. IEEE, 2019.
  21. Khoat Than, Xuan Bui, Tung Nguyen-Trong, Khang Truong, Son Nguyen, Bach Tran, Linh Ngo Van, and Anh Nguyen-Duc. “How to make a machine learn continuously: a tutorial of the Bayesian approach.” In Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, vol. 11006, p. 110060I. 2019.
  22. Duc-Anh Nguyen, Kim Anh Nguyen, Ngo Van Linh, Khoat Than, “Keeping priors in streaming Bayesian learning”, In Proceedings of the 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 247-258, 2017.
  23. Vu Le, Chien Phung, Cuong Vu, Ngo Van Linh, Khoat Than, “Streaming Aspect-Sentiment Analysis”, in Proceeding of the International Conference on Computing and Communication Technologies (RIVF), pp 181-186, 2016
  24. Mai Tien Khai, Mai Anh Sang, Nguyen Kim Anh, Ngo Van Linh, Khoat Than, “Enabling Hierarchical Dirichlet Processes to work better for short texts at large scale” in Proceeding of the 20th Pacific-Asia Conference (PAKDD), pp. 431-442, 2016.
  25. Ngo Van Linh, Nguyen Kim Anh, Khoat Than, and Nguyen Nguyen Tat. ”Effective and Interpretable Document Classification Using Distinctly Labeled Dirichlet Process Mixture Models of von Mises-Fisher Distributions” In proceeding of 20th Database Systems for Advanced Applications Conference (DASFAA), pp. 139-153, 2015.
  26. Ngo Van Linh, Nguyen Kim Anh, and Khoat Than. "An Effective NMF-Based Method for Supervised Dimension Reduction" Knowledge and Systems Engineering (KSE), pp.93-104, 2015.
  27. Anh Nguyen Kim, Nguyen Khac Toi, and Ngo Van Linh. "An interpretable method for text summarization based on simplicial non-negative matrix factorization" in Proceeding of the Symposium on Information and Communication Technology (SoICT), pp.57-64, 2014.
  28. Nguyen Thi Kim Anh, Ngo Van Linh, Nguyen Khac Toi, Nguyen The Tam, "Multi-labeled Document Classification using Semi-supervised Mixture Model of Watson distributions on Document Manifold" In proceeding of the International Conference of Soft Computing and Pattern Recognition (SoCPaR), pp.129-134, 2013.
  29. Nguyen Thi Kim Anh, Nguyen The Tam, Ngo Van Linh, "Document Clustering using Mixture Model of von Mises-Fisher Distributions on Document Manifold" In proceeding of the International Conference of Soft Computing and Pattern Recognition (SoCPaR), pp. 146-151, 2013.
  30. Nguyen Kim Anh, Ngo Van Linh, Le Hong Ky, Nguyen The Tam, "Document classification using semi-supervised mixture model of von Mises-Fisher distributions on document manifold" In proceeding of the Symposium on Information and Communication Technology (SoICT), pp. 94-100, 2013.
  31. Nguyen Kim Anh, Nguyen The Tam, Ngo Van Linh, "Document clustering using dirichlet process mixture model of von Mises-Fisher distributions" In proceeding of the Symposium on Information and Communication Technology (SoICT), pp. 131-138, 2013.
  32. Ngo Van Linh, Nguyen Kim Anh, Cao Manh Dat, "Improving Vietnamese Web Page Classification by Combining Hybrid Feature Selection and Label Propagation with Link Information" In Proceeding of the International Conference on Context-Aware Systems and Applications (ICCASA), pp.324-334, 2012.
  33. Nguyen Kim Anh, Vu Minh Thanh, Ngo Van Linh, "Efficient label propagation for classification on information networks" In proceeding of the Symposium on Information and Communication Technology (SoICT), pp. 41-46, 2012.

Teaching